This thesis considers the real-time implementation phases of a multiple-input multiple-output (MIMO) wireless communication system. The parts which are related to the implementation detail the blocks realized on a field programmable gate array (FPGA) board and define the connections between these blocks and typical radio frequency front-end modules assisting the wireless communication. Two sides of the implemented communication testbed are discussed separately as the transmitter and the receiver parts. In addition to usual building blocks of the transmitter and the receiver blocks, a special type of iterative parallelized decoding architecture has also been implemented on the testbed to demonstrate its potential in low-latency communication systems. In addition to practical aspects, this thesis also presents theoretical findings for an improved version of the built system using analytical tools and simulation results for possible extensions to orthogonal frequency division multiplexing (OFDM).

The need for reliable, high-throughput, mobile wireless communication technologies has never been greater as increases in the demand for on-the-go access to information, entertainment, and other electronic services continues. Two such technologies, which are at the forefront of current research efforts, are orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) systems, their union being known simply as MIMO-OFDM. The successful performance of these technologies depends upon the availability of accurate information concerning the wireless communication channel. In this dissertation, several issues related to quality of this channel state information (CSI) are studied. Specifically, the first part of this dissertation considers the design of optimal pilot signals for OFDM systems. The optimization is addressed via lower bounds on the estimation error variance, which bounds are given by formulations of the Cram'{e}r-Rao bound (CRB). The second part of this dissertation uses the CRB once again, this time as a tool for evaluating the potential performance of MIMO-OFDM channel estimation and prediction. Bounds are found for several parametric time-varying wideband MIMO-OFDM channel models, and numerical evaluations of these bounds are used to illuminate several interesting features regarding the estimation and prediction of MIMO-OFDM channels. The final part of this dissertation considers the problem of MIMO multiplexing using SVD-based methods when only imperfect CSI is available. For this purpose, general per-MIMO-subchannel signal and interference-plus-noise power expressions are derived to quantify the effects of CSI imperfections, and these expressions are then used to find robust MIMO-SVD power and bit allocations which maintain good overall performance in spite of imperfect CSI.

FundaÃÃo de Amparo à Pesquisa do Estado do Cearà / Atualmente a internet à uma ferramenta largamente utilizada e o grande desenvolvimentoe popularidade de tecnologias de acesso sem-fio (wireless) nos levam a um futuro no qual uma conexÃo caracterizada por estar disponÃvel âanytime, anywhereâ, ou seja, a qualquer hora e em qualquer lugar, serà essencial. Tal caracterÃstica à considerada obrigatÃria em sistemas4G (quarta geraÃÃo), mas para uma experiÃncia satisfatÃria para o usuÃrio à necessÃrio que uma conexÃo segura e eficiente esteja disponÃvel. A fim de obter tal eficiÃncia, a comunidade de pesquisa tem gerado algumas soluÃÃes promissoras que obtÃm ganhos significativos no desempenho do sistema, tais como modulaÃÃo e codificaÃÃo adaptativas, codificaÃÃo espaÃo-temporal, mÃltiplas antenas e canais MIMO (Multiple Input Multiple Output ), modulaÃÃo multiportadora, detecÃÃo multiusuÃrio, etc. [1]. Dentre essas soluÃÃes, destaca-se a adaptaÃÃo do sistema, ou seja, o sistema deve estar em constante adaptaÃÃo para obter sempre o melhor desempenho possÃvel para cada situaÃÃo em que se encontra. No entanto, uma importante premissa para a adaptaÃÃo do sistema consiste em conhecer o estado atual em que o sistema se encontra (informaÃÃo sobre o canal de comunicaÃÃo). Para isso diversas tÃcnicas de estimaÃÃo de canal sÃo propostas na literatura, cada uma possuindo vantagens e desvantagens. Nesse trabalho o impacto da estimaÃÃo de canal na adaptaÃÃo de enlace à analisado atravÃs de simulaÃÃes computacionais1. Em particular, duas tÃcnicas de estimaÃÃo de canal com caracterÃsticas diferentes sÃo analisadas, para alguns cenÃrios especÃficos em um sistema MIMO-OFDM (Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing ), atravÃs de uma mÃtrica que considera tanto a redundÃncia introduzida para estimar o canal quanto o erro de estimaÃÃo de canal de cada tÃcnica. Os resultados encontrados constituem curvas que podem ser utilizadas para efetuar a adaptaÃÃo de enlace do sistema de maneira mais realista, ou seja, considerando o efeito da estimaÃÃo de canal, alÃm de incluir a prÃpria tÃcnica de estimaÃÃo de canal como um parÃmetro a ser adaptado. / Atualmente a internet à uma ferramenta largamente utilizada e o grande desenvolvimentoe popularidade de tecnologias de acesso sem-fio (wireless) nos levam a um futuro no qual uma conexÃo caracterizada por estar disponÃvel âanytime, anywhereâ, ou seja, a qualquer hora e em qualquer lugar, serà essencial. Tal caracterÃstica à considerada obrigatÃria em sistemas4G (quarta geraÃÃo), mas para uma experiÃncia satisfatÃria para o usuÃrio à necessÃrio que uma conexÃo segura e eficiente esteja disponÃvel. A fim de obter tal eficiÃncia, a comunidade de pesquisa tem gerado algumas soluÃÃes promissoras que obtÃm ganhos significativos no desempenho do sistema, tais como modulaÃÃo e codificaÃÃo adaptativas, codificaÃÃo espaÃo-temporal, mÃltiplas antenas e canais MIMO (Multiple Input Multiple Output ), modulaÃÃo multiportadora, detecÃÃo multiusuÃrio, etc. [1]. Dentre essas soluÃÃes, destaca-se a adaptaÃÃo do sistema, ou seja, o sistema deve estar em constante adaptaÃÃo para obter sempre o melhor desempenho possÃvel para cada situaÃÃo em que se encontra. No entanto, uma importante premissa para a adaptaÃÃo do sistema consiste em conhecer o estado atual em que o sistema se encontra (informaÃÃo sobre o canal de comunicaÃÃo). Para isso diversas tÃcnicas de estimaÃÃo de canal sÃo propostas na literatura, cada uma possuindo vantagens e desvantagens. Nesse trabalho o impacto da estimaÃÃo de canal na adaptaÃÃo de enlace à analisado atravÃs de simulaÃÃes computacionais1. Em particular, duas tÃcnicas de estimaÃÃo de canal com caracterÃsticas diferentes sÃo analisadas, para alguns cenÃrios especÃficos em um sistema MIMO-OFDM (Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing ), atravÃs de uma mÃtrica que considera tanto a redundÃncia introduzida para estimar o canal quanto o erro de estimaÃÃo de canal de cada tÃcnica. Os resultados encontrados constituem curvas que podem ser utilizadas para efetuar a adaptaÃÃo de enlace do sistema de maneira mais realista, ou seja, considerando o efeito da estimaÃÃo de canal, alÃm de incluir a prÃpria tÃcnica de estimaÃÃo de canal como um parÃmetro a ser adaptado. / Nowadays the internet is a widely used tool and the great development and popularity of wireless technologies leads us to a future where the connectivity will be characterized as âanywhere, anytimeâ. Such characteristic is considered essential in 4G systems. However, for a satisfactory user experience a secure and efficient connectivity has to be always available. To obtain such efficiency, the research community has generated a number of promising solutions that achieve significative improvements in system performance, such as adaptive modulation and coding, space-time coding, multiple antennas and MIMO (Multiple Input Multiple Output ) channels, multicarrier modulation, multiuser detection, etc. [1]. Among these solutions, the system adaptation is a particularly interesting one, there is, the system must constantly adapt itself to achieve the best performance for each situation. However, one important premise for the system adaptation is the knowledge of the channel state information (CSI). To obtain this knowledge, several channel estimation strategies were proposed in the literature, each one with advantages and disadvantages. In this work we analyze the impact of channel estimation in the link adaptation through computer simulations1. Two channel estimation techniques with different characteristics were analyzed for some specific scenarios in a MIMO-OFDM (Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing ) system. To perform the analysis it was used a metric that consider the redundancy introduced to estimate the channel and the channel estimation error of each technique. The obtained results constitute curves that can be used to perform link adaptation in a more realistic way, that is, considering the effect of channel estimation. Besides, it is shown that even the choice of the channel estimation strategy can be an adaptable parameter so that the most adequate channel estimation strategy for each system state is used. / Nowadays the internet is a widely used tool and the great development and popularity of wireless technologies leads us to a future where the connectivity will be characterized as âanywhere, anytimeâ. Such characteristic is considered essential in 4G systems. However, for a satisfactory user experience a secure and efficient connectivity has to be always available. To obtain such efficiency, the research community has generated a number of promising solutions that achieve significative improvements in system performance, such as adaptive modulation and coding, space-time coding, multiple antennas and MIMO (Multiple Input Multiple Output ) channels, multicarrier modulation, multiuser detection, etc. [1]. Among these solutions, the system adaptation is a particularly interesting one, there is, the system must constantly adapt itself to achieve the best performance for each situation. However, one important premise for the system adaptation is the knowledge of the channel state information (CSI). To obtain this knowledge, several channel estimation strategies were proposed in the literature, each one with advantages and disadvantages. In this work we analyze the impact of channel estimation in the link adaptation through computer simulations1. Two channel estimation techniques with different characteristics were analyzed for some specific scenarios in a MIMO-OFDM (Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing ) system. To perform the analysis it was used a metric that consider the redundancy introduced to estimate the channel and the channel estimation error of each technique. The obtained results constitute curves that can be used to perform link adaptation in a more realistic way, that is, considering the effect of channel estimation. Besides, it is shown that even the choice of the channel estimation strategy can be an adaptable parameter so that the most adequate channel estimation strategy for each system state is used.

L’estimation de canal joue un rôle important dans les communications mobiles sans fil et en particulier dans les systèmes multi-antennes MIMO. Contrairement aux techniques classiques d’estimation de canal basées sur des séquences d’apprentissage ou des symboles pilotes, les techniques aveugles ne nécessitent aucune insertion de symboles d'apprentissage et permettent d'augmenter le débit utile. Les principales difficultés des techniques aveugles résident dans l’ambiguïté présente sur les estimées. Les techniques d’estimation semi-aveugles, basées sur les mêmes méthodes que l’estimation aveugle, sont plus robustes. Elles exploitent l’information aveugle ainsi que l’information provenant d’un nombre réduit de symboles d’apprentissage. Cette estimation du canal de communication est très utile dans les systèmes MIMO et permet de précoder le signal MIMO-OFDM en lui appliquant un pré-mélange permettant d'améliorer les performances. De nombreux types de précodeurs existent et leurs performances varient en fonction des critères d'optimisation retenus (Water-Filling, MMSE, Equal Error, max-SNR, max-d min …), mais aussi avec la qualité de l'estimation du canal de communication. Nous étudions dans cette thèse l’impact de l’utilisation de l’information du canal (CSI) provenant des méthodes d’estimation aveugle et semi-aveugle, dans l’application des précodeurs linéaires MIMO. Nous présentons également une étude statistique de l’erreur d’estimation provenant de ces méthodes. L’optimisation de ces précodeurs nous mène par la suite à exploiter un autre procédé permettant l’amélioration des performances : les codes correcteurs d’erreur. Nous nous intéressons particulièrement aux codes LDPC non-binaires et leur association avec les précodeurs linéaires MIMO. Nous montrons qu’une adaptation est possible et s’avère bénéfique dans certains cas. L’optimisation de cette association nous a permis de proposer un nouveau précodeur basé sur la maximisation de l’information mutuelle, robuste et plus performant. / Channel estimation plays an important role in wireless mobile communications, especially in MIMO systems. Unlike conventional channel estimation techniques based on training sequences or pilot symbols, blind techniques does not require the insertion of training symbols and allow higher throughput. The main problems of the blind lies in the ambiguity over the estimated channel. Based on the same methods as the blind estimation, the semi-blind estimation techniques are more robust. They exploit the blind information along with information provided by a small number of training symbols. The channel estimation is useful in MIMO systems and allows the precoding of the MIMO-OFDM signal by applying a pre-mixture in order to improve performance. Many types of precoders exist and their performance varies depending not only on the optimization criteria (Water-Filling, MMSE, Equal Error, max-SNR, max-d min ...), but also on the estimated channel. In this thesis we study the impact of using the channel information (CSI) from the blind and semi-blind estimation techniques to apply MIMO linear precoders. We also present a statistical study of the estimation error of these methods. The optimization of these precoders leads eventually to use another process allowing more performance improvement: the error correcting codes. We are particularly interested in non-binary LDPC codes and their association with linear MIMO precoders. We show that a matching is possible, and is beneficial in some cases. The optimization of this combination has allowed us to propose a new robust and more efficient precoder based on the maximization of mutual information.

The interest in wireless communications among consumers has exploded since the introduction of the "3G" cell phone standards. One reason for their success is the increasingly higher data rates achievable through the networks. A further increase in data rates is possible through the use of multiple antennas at either or both sides of the wireless links. Precoding and receive filtering using matrices obtained from a singular value decomposition (SVD) of the channel matrix is a transmission strategy for achieving the channel capacity of a deterministic narrowband multiple-input multiple-output (MIMO) communications channel. When signalling over wideband channels using orthogonal frequency-division multiplexing (OFDM), an SVD must be performed for every sub-carrier. As the number of sub-carriers of this traditional approach grow large, so does the computational load. It is therefore interesting to study alternate means for obtaining the decomposition. A wideband MIMO channel can be modeled as a matrix filter with a finite impulse response, represented by a polynomial matrix. This thesis is concerned with investigating algorithms which decompose the polynomial channel matrix directly. The resulting decomposition factors can then be used to obtain the sub-carrier based precoding and receive filtering matrices. Existing approximative polynomial matrix QR and singular value decomposition algorithms were modified, and studied in terms of decomposition quality and computational complexity. The decomposition algorithms were shown to give decompositions of good quality, but if the goal is to obtain precoding and receive filtering matrices, the computational load is prohibitive for channels with long impulse responses. Two algorithms for performing exact rational decompositions (QRD/SVD) of polynomial matrices were proposed and analyzed. Although they for simple cases resulted in excellent decompositions, issues with numerical stability of a spectral factorization step renders the algorithms in their current form purposeless. For a MIMO channel with exponentially decaying power-delay profile, the sum rates achieved by employing the filters given from the approximative polynomial SVD algorithm were compared to the channel capacity. It was shown that if the symbol streams were decoded independently, as done in the traditional approach, the sum rates were sensitive to errors in the decomposition. A receiver with a spatially joint detector achieved sum rates close to the channel capacity, but with such a receiver the low complexity detector set-up of the traditional approach is lost. Summarizing, this thesis has shown that a wideband MIMO channel can be diagonalized in space and frequency using OFDM in conjunction with an approximative polynomial SVD algorithm. In order to reach sum rates close to the capacity of a simple channel, the computational load becomes restraining compared to the traditional approach, for channels with long impulse responses.

OFDM is a promising technique for high-data-rate wireless communications because it can combat inter-symbol interference (ISI) caused by the dispersive fading of wireless channels. The proposed research focuses on techniques that improve the performance of OFDM-based wireless communications and its commercial and military applications. In particular, we address the following aspects of OFDM: inter-channel interference (ICI) suppression, interference suppression for clustered OFDM, clustered OFDM based anti-jamming modulation, channel estimation for MIMO-OFDM, MIMO transmission with limited feedback. For inter-channel interference suppression, a frequency domain partial response coding (PRC) scheme is proposed to mitigate ICI. We derive the near-optimal weights for PRC that is independent on the channel power spectrum. The error floor resulting from ICI can be reduced significantly using a two-tap or a three-tap PRC. Clustered OFDM is a new technique that has many advantages over traditional OFDM. In clustered OFDM systems, adaptive antenna arrays are used for interference suppression. To calculate weights for interference suppression, we propose a polynomial-based parameter estimator to combat the severe leakage of the DFT based estimator due to the small size of the cluster. An adaptive algorithm is developed to obtain optimal performance. For high data rate military communications, we propose a clustered OFDM base spread spectrum modulation to provide both anti-jamming and fading suppression capability. We analyze the performance of uncoded and coded system. Employing multiple transmit and receive antennas in OFDM systems (MIMO-OFDM) can increase the spectral efficiency and link reliability. We develop a minimum mean-square-error (MMSE) channel estimator that takes advantage of the spatial-frequency correlations in MIMO-OFDM systems to minimize the estimation error. We investigate the training sequence design and two optimal training sequence designs are given for arbitrary spatial correlations. For a MIMO system, the diversity and array gains can be obtained by exploiting channel information at the transmitter. For MIMO-OFDM systems, we propose a subspace tracking based approach that can exploit the frequency correlations of the OFDM system to reduce the feedback rate. The proposed approach does not need recalculate the precoding matrix and is robust to multiple data stream transmission.

This research investigates techniques for iterative channel estimation to maximize channel capacity and communication security. The contributions of this dissertation are as follows: i) An accurate, low-complexity approach to pilot-assisted fast-fading channel estimation for single-carrier modulation with a turbo equalizer and a decoder is proposed. The channel is estimated using a Kalman filter (KF) followed by a zero-phase filter (ZPF) as a smoother. The combination of the ZPF with the KF of the channel estimator makes it possible to reduce the estimation error to near the Wiener bound. ii) A new semi-blind channel estimation technique is introduced for multiple-input-multiple-output channels. Once the channel is estimated using a few pilots, a low-order KF is employed to progressively predict the channel gains for the upcoming blocks. iii) The capacity of radio channels is investigated when iterative channel estimation, data detection, and decoding are employed. By taking the uncertainty in decoded data bits into account, the channel Linear Minimum Mean Square Error (LMMSE) estimator of an iterative receiver with a given pilot ratio is obtained. The derived error value is then used to derive a bound on capacity. It is shown that in slow fading channels, iterative processing provides only a marginal advantage over non-iterative approach to channel estimation. Knowing the capacity gain from iterative processing versus purely pilot-based channel estimation helps a designer to compare the performance of an iterative receiver against a non-iterative one and select the best balance between performance and cost. iv) A Radio channel is characterized by random parameters which can be used to generate shared secret keys by the communicating parties when the channel is estimated. This research studies upper bounds on the rate of the secret keys extractable from iteratively estimated channels. Various realistic scenarios are considered where the transmission is half-duplex and/or the channel is sampled under the Nyquist rate. The effect of channel sampling interval, fading rate and noise on the key rate is demonstrated. The results of this research can be beneficial for the design and analysis of reliable and secure mobile wireless systems. / Graduate / 0544

Abstract Radio resource management techniques for broadband wireless systems beyond the existing cellular systems are developed while considering their special characteristics such as multi-carrier techniques, adaptive radio links and multiple-input multiple-output (MIMO) antenna techniques. Special focus is put on the design of linear transmission strategies in a cooperative cellular system where signal processing can be performed in a centralised manner across distributed base station (BS) antenna heads. A time-division duplex cellular system based on orthogonal frequency division multiplexing (OFDM) with adaptive MIMO transmission is considered in the case where the received signals are corrupted by non-reciprocal inter-cell interference. A bandwidth efficient closed-loop compensation algorithm combined with interference suppression at the receiver is proposed to compensate for the interference and to guarantee the desired Quality of Service (QoS) when the interference structure is known solely at the receiver. A greedy beam ordering and selection algorithm is proposed to maximise the sum rate of a multiuser MIMO downlink (DL) with a block zero forcing (ZF) transmission. The performance of the block-ZF transmission combined with the greedy scheduling is shown to approach the sum capacity as the number of users increases. The maximum sum rate is often found to be achieved by transmitting to a smaller number of users or beams than the spatial dimensions allow. In addition, a low complexity algorithm for joint user, bit and power allocation with a low signalling overhead is proposed. Different linear transmission schemes, including the ZF as a special case, are developed for the scenario where the cooperative processing of the transmitted signal is applied to users located within a soft handover (SHO) region. The considered optimisation criteria include minimum power beamformer design; balancing the weighted signal-to-interference-plus-noise ratio (SINR) values per data stream; weighted sum rate maximisation; and balancing the weighted rate per user with additional QoS constraints such as guaranteed bit rate per user. The method can accommodate supplementary constraints, e.g., per antenna or per BS power constraints, and upper/lower bounds for the SINR values of the data streams. The proposed iterative algorithms are shown to provide powerful solutions for difficult non-convex transceiver optimisation problems. System level evaluation is performed in order to assess the impact of a realistic multi-cell environment on the performance of a cellular MIMO-OFDM system. The users located in the SHO region are shown to benefit from greatly increased transmission rates. Consequently, significant overall system level gains result from cooperative SHO processing. The proposed SHO scheme can be used for providing a more evenly distributed service over the entire cellular network.

In this dissertation, channel estimation and channel prediction are studied for wireless communication systems. Wireless communication for time-variant channels becomes more important by the fast development of intelligent transportation systems which motivates us to propose a reduced rank channel estimator for time-variant frequency-selective high-speed railway (HSR) systems and a reduced rank channel predictor for fast time-variant flat fading channels. Moreover, the potential availability of large bandwidth channels at mm-wave frequencies and the small wavelength of the mm-waves, offer the mm-wave massive multiple-input multiple-output (MIMO) communication as a promising technology for 5G cellular networks. The high fabrication cost and power consumption of the radio frequency (RF) units at mm-wave frequencies motivates us to propose a low-power hybrid channel estimator for mm-wave MIMO orthogonal frequency-division multiplexing (OFDM) systems. The work on HSR channel estimation takes advantage of the channel's restriction to low dimensional subspaces due to the time, frequency and spatial correlation of the channel and presents a low complexity linear minimum mean square error (LMMSE) estimator for MIMO-OFDM HSR channels. The channel estimator utilizes a four-dimensional (4D) basis expansion channel model obtained from band-limited generalized discrete prolate spheroidal (GDPS) sequences. Exploiting the channel's band-limitation property, the proposed channel estimator outperforms the conventional interpolation based least square (LS) and MMSE estimators in terms of estimation accuracy and computational complexity, respectively. Simulation results demonstrate the robust performance of the proposed estimator for different delay, Doppler and angular spreads. Channel state information (CSI) is required at the transmitter for improving the performance gain of the spatial multiplexing MIMO systems through linear precoding. In order to avoid the high data rate feedback lines, which are required in fast time-variant channels for updating the transmitter with the rapidly changing CSI, a subframe-wise channel tracking scheme is presented. The proposed channel predictor is based on an assumed DPS basis expansion model (DPS-BEM) for exploiting the variation of the channel coefficients inside each sub-frame and an autoregressive (AR) model of the basis coefficients over each transmitted frame. The proposed predictor properly exploits the channel's restriction to low dimensional subspaces for reducing the prediction error and the computational complexity. Simulation results demonstrate that the proposed channel predictor out-performs the DPS based minimum energy (ME) predictor for different ranges of normalized Doppler frequencies and has better performance than the conventional Wiener predictor for slower time-variant channels and almost the similar performance to it for very fast time-variant channels with the reduced amount of computational complexity. The work on the hybrid mm-wave channel estimator considers the sparse nature of the mm-wave channel in angular domain and leverages the compressed sensing (CS) tools for recovering the angular support of the MIMO-OFDM mm-wave channel. The angular channel is treated in a continuous framework which resolves the limited angular resolution of the discrete sparse channel models used in the previous CS based channel estimators. The power leakage problem is also addressed by modeling the continuous angular channel as a multi-band signal with the bandwidth of each sub-band being proportional to the amount of power leakage. The RF combiner is designed to be implemented using a network of low-power switches for antenna subset selection based on a multi-coset sampling pattern. Simulation results validate the effectiveness of the proposed hybrid channel estimator both in terms of the estimation accuracy and the RF power consumption. / Graduate

This work deals with the design of MT transmit, MR receive antenna MIMO (Multiple Input Multiple Output) communication system where the transmitter performs a linear operation on data. This linear precoding model includes systems which involve signal shaping for achieving higher data rates, uncoded MIMO Multicarrier and Single-Carrier systems and, the more recent, MIMO-OFDM (Orthogonal Frequency Division Multiplexing) systems employing full diversity Space-Frequency codes. The objective of this work is to design diversity centric and rate centric linear precoded MIMO systems whose performance is better than the existing designs. In particular, we consider MIMO-OFDM systems, Zero Padded MIMO systems and MIMO systems with limited rate feedback. Design of full diversity MIMO-OFDM systems of rate symbol per channel use (1 s/ pcu) : In literature, MIMO-OFDM systems exploiting full diversity at a rate of 1 s/ pcu are based on a few specific Space-Frequency (SF)/ Space-Time-Frequency (STF) codes. In this work, we devise a general parameterized framework for the design of MIMO-OFDM systems employing full diversity STF codes of rate 1 s/ pcu. This framework unifies all existing designs and provides tools for the design of new systems with interesting properties and superior performance. Apart from rate and diversity, the parameters of the framework are designed for a low complexity receiver. The parameters of the framework usually depend on the channel characteristics (number of multipath, Delay Profile (DP)). When channel characteristics are available at the transmitter, a procedure to optimize the performance of STF codes is provided. The resulting codes are termed as DP optimized codes. Designs obtained using the optimization are illustrated and their performance is shown to be better than the existing ones. To cater to the scenarios where channel characteristics are not available at the transmitter, a complete characterization of a class of full diversity DP Independent (DPI) STF codes is provided. These codes exploit full diversity on channels with a given number of multipath irrespective of their characteristics. Design of DP optimized STF codes and DPI codes from the same framework highlights the flexibility of the framework. Design of Zero Padded (ZP) MIMO systems : While the MIMO-OFDM transmitter needs to precode data for exploiting channel induced multipath diversity, ZP MIMO systems with ML receivers are shown to exploit multipath diversity without any precoding. However, the receiver complexity of such systems is enormous and hence a study ZP MIMO system with linear receivers is undertaken. Central to this study involves devising low complexity receivers and deriving the diversity gain of linear receivers. Reduced complexity receiver implementations are presented for two classes of precoding schemes. An upper bound on the diversity gain of linear receivers is evaluated for certain precoding schemes. For uncoded systems operating on a channel of length L, this bound is shown to be MRL_MT +1 for uncoded transmissions, i.e, such systems tend to exploit receiver and multipath diversities. On the other hand, MIMO-OFDM systems designed earlier have to trade diversity with receiver complexity. These observations motivate us to use ZP MIMO systems with linear receivers for channels with large delay spread when receiver complexity is at a premium. Design examples highlighting the attractiveness of ZP systems when employed on channels with large delay spread are also presented. Efficient design of MIMO systems with limited feedback : Literature presents a number of works that consider the design of MIMO systems with partial feedback. The works that consider feedback of complete CSI, however, do not provide for an efficient system design. In this work, we consider two schemes, Correlation matrix feedback and Channel information feedback that convey complete CSI to the transmitter. This CSI is perturbed due to various impairments. A perturbation analysis is carried out to study the variations in mutual information for each of the proposed schemes. For ergodic channels, this analysis is used to design a MIMO system with a limited rate feedback. Using a codebook based approach, vector quantizers are designed to minimize the loss in ergodic capacity for each of the proposed schemes. The efficiency of the design stems from the ability to obtain closed-form expression for centroids during the iterative vector quantizer design. The performance of designed vector quantizers compare favorably with the existing designs. The vector quantizer design for channel information feedback is robust in the sense that the same codebook can be used across all operating SNR. Use of vector quantizers for improving the outage performance is also presented.